Unexpected epidemic thresholds in heterogeneous networks: The role of disease transmission
Unexpected epidemic thresholds in heterogeneous networks: The role of disease transmission
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DOI：
10.1103/physreve.70.030902
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发表时间：
2004-09-01
影响因子：
2.4
通讯作者：
Stone, L
中科院分区：
文献类型：
--
作者：
Olinky, R;Stone, L
我们重新制定了最近对高度异构网络上感染过程的几个分析（例如，无标度网络）得出结论，即使传播概率非常小，疾病也会传播并持续下去。后一种研究的结果与传统的流行病学模型形成对照，后者存在明显的阈值效应，即如果传播概率低于临界阈值水平，则疾病预计会消亡。在这里，我们表明，流行病的传播同样取决于感染方案以及网络结构。连接性依赖的感染方案可以产生阈值效应，即使在无标度网络中，否则他们会是意想不到的。
We reformulate several recent analyses of infection processes on highly heterogeneous networks (e.g., scale-free networks) which conclude that diseases will spread and persist even for vanishingly small transmission probabilities. The results of these latter studies contrast with conventional epidemiological models where there are clear threshold effects, namely, should the transmission probability fall below a critical threshold level the disease is expected to die out. Here we show that epidemic propagation depends equally on the infection scheme as well as the network structure. Connectivity-dependent infection schemes can yield threshold effects even in scale-free networks where they would otherwise be unexpected.